Use of machine learning for analyzing companies enlisted in stock market
In one way the answer is NO. You can't incorporate all the necessary details in an AI program to correctly predict the financial market, at least not in currently. A particular event is a result of many actions and events from the past. Everything is like a chain.
You might have heard of the ButterFly Effect. It simply states that small things can have very large effects. Like flap of butterfly's wings leading to a hurricane. You can read more about it here.
Now back to your question. I believe you are somewhat familiar with the financial system and stocks. Close your eyes and try to imagine all the data that is being churned into machines. Apart from that, there are many decisions that lead to changes in the financial market directly. Like policies made by the government deals bagged by the company related to imports and exports, death of the main employee (like CEO, founder), and other many things. Apart from that, there are uncountable things that indirectly affect the market. I want you to think about it for a while. Now consider doing this for all the stocks present. After even stock values of one are dependent on the others in one way or another.
This amount of data, in other ways considering all these things, is not possible for current generation computers to process. You might have a hit with quantum computers coming though.
Now what you can do, is try to make a Deep Network (with Reinforcement Learning) that can predict the behavior and shift in the direction of some stocks. For example, whether it will go up for down or try to keep a constant line on the graph.
Selection of Features is always an important key to the success of Machine Learning algorithms. Another problem that stock market-related AI programs face is that Economics is itself an emerging and novice field of science. It's not as mature as physics, chemistry or biology. Thus finding out and deciding over the choice of features is another difficult job.
I found this paper online. Haven't given a look to it but, I believe this might help you a bit.